In this course provides an introduction to the theory, methods and practice of regression analysis and time series. The goals are (a) to understand basic regression designs, (b) design and carry out studies that use regression techniques and basic time series techniques, (c) prepare to learn more about more advanced statistical procedures, (d) read and understand professional literature that uses regression analysis.
The course assumes a working knowledge of elementary statistical concepts and techniques.
The focus of the course is the study of simple and multiple linear regression models. We will also look at non--linear models: logistic regression and Poisson regression. We will also study basic time series models.
We will have four exams each worth 20% of your grade. In order to pass the course, you need to obtain an average of 50% or more and not obtain grades below 30%. I will also assign projects worth 20% of your grade.
As a requisite, you need to become familiar with WebCT and a computer based statistical package. I'll be using Maple Student Edition, but you can use or free distribution packages.